AimPrevious studies have shown that warming temperatures can affect the phenology of cold deciduous forests, delaying the timing of leaf coloration. However, these works have principally been based on observations from a small number of sites. Consequently it has been challenging to infer continental-scale variations in the phenology of individual deciduous forest species and the extent to which there may be underlying climate drivers for these variations. To address that problem, this study evaluated and predicted the large-scale variations of leaf colouring by using macroscale observations and models. Location North America. Methods We developed leaf colouring models using select observations (1) from Harvard Forest only and (2) from both Harvard Forest and a new, ground-based, Alaskan dataset from the USA National Phenology Network (USA-NPN). Both model types were evaluated using reserved observations from the continental-scale USA-NPN thatwere not used inmodel calibration.Validated modelswere then used to assess the spatial scaling and interspecies variation in the timing of leaf coloration. The sensitivity of the models to projected climate change was also evaluated. Results Using a model calibrated only with data from Harvard Forest, significant biases were found in predictions of leaf colouring date for species with broad habitat ranges in the temperate to boreal regions.When calibration data from both Harvard Forest and Alaska were used, model performance improved throughout the whole continent. It was also found that species with similar shade tolerance could be described by similar models. Finally, the models indicated that climate change over the next century will affect leaf coloration in Alaska less than in the Harvard Forest region. Main conclusions For a given species, continental-scale variations in the timing of autumn leaf coloration can be predicted using a model driven by photoperiod and daily temperature. The temperature sensitivity of the leaf colouring date is nonlinear, such that warmer regions have a larger temperature sensitivity than cooler regions. Species-specific measurements from multiple environments are essential for model parameterization. Keywords Autumn phenology, climate change, deciduous trees, leaf coloration, phenology models, scaling.

Seasonal variation in photosynthetic capacity is an important part of the overall seasonal variability of temperate deciduous forests. However, it has only recently been introduced in a few terrestrial biosphere models, and many models still do not include it. The biases that result from this omission are not well understood. In this study, we use the Ecosystem Demography 2 model to simulate an oak-dominated stand in the New Jersey Pine Barrens. Two alternative model configurations are presented, one with seasonal variation of photosynthetic capacity (SPC-ON) and one without seasonal variation of photosynthetic capacity (SPC-OFF). Under typical climate conditions, the two configurations simulate values of monthly gross primary productivity (GPP) as different as 0.05 kg C m−2 month−1 in the early summer and 0.04 kg C m−2 month−1 in the fall. The differences between SPC-ON and SPC-OFF are amplified when there is temporal correlation between photosynthetic capacity and climate anomalies or disturbances. Warmer spring temperatures enhance GPP in SPC-ON more than in SPC-OFF, but warmer fall temperatures enhance GPP in SPC-OFF more than in SPC-ON. Defoliation by gypsy moth, a class of disturbance that typically happens in late spring in the New Jersey Pine Barrens, has a disproportionately negative impact on GPP in SPC-ON. It is concluded that including seasonal variation of photosynthetic capacity in models will improve simulations of monthly scale ecosystem functioning as well as of longer-term responses to climate change and disturbances.

A new framework for understanding the macro‐scale variations in spring phenology is developed by using new data from the USA National Phenology Network. Changes in spring budburst for the United States are predicted by using Coupled Model Intercomparison Project phase 5 outputs. Macro‐scale budburst simulations for the coming century indicate that projected warming leads to earlier budburst by up to 17 days. The latitudinal gradient of budburst becomes less pronounced due to spatially varying sensitivity of budburst to climate change, even in the most conservative emissions scenarios. Currently existing interspecies differences in budburst date are predicted to become smaller, indicating the potential for secondary impacts at the ecosystem level. We expect that these climate‐driven changes in phenology will have large effects on the carbon budget of U.S. forests and these controls should be included in dynamic global vegetation models.